We explore the prediction accuracy of two strategies that designers use to predict consumer evaluations of novel product designs: categorization-based strategy and sequential learning strategy. Two studies support that the latter strategy outperforms the former strategy and that the latter strategy performs better when data are presented in multiple sets than when presented in a single set.